MAnorm2 Tools for Normalizing and Comparing ChIP-seq Samples
Introduction
Eukaryotic gene transcription is regulated by a large cohort of chromatin associated proteins, and inferring their differential binding sites between cellular contexts requires a rigorous comparison of the corresponding ChIP-seq samples. The package MAnorm2 is primarily developed for quantitatively comparing groups of ChIP-seq samples (e.g., groups of biological replicates corresponding to different cellular contexts). Technically, MAnorm2 uses a hierarchical strategy for normalization of ChIP-seq samples, and it assesses within-group variability of ChIP-seq signals under an empirical Bayes framework, in which MAnorm2 considers the abundance of differential ChIP-seq signals between groups of samples and the possibility of different within-group variability between groups. Another capability of MAnorm2 is to identify hypervariable ChIP-seq signals across samples, which, for example, is essential to dissecting the epigenetic heterogeneity across cancer patients as well as revealing potential sub-structures associated with them.
Publications
MAnorm2 for quantitatively comparing groups of ChIP-seq samples
Cite thisCited by 8 (Google Schoolar as of January 16, 2023)HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples
Cite thisCited by 0 (Google Schoolar as of January 16, 2023)
Credits
- Shiqi Tu tushiqi@sinh.ac.cn InvestigatorDeveloper
Regulatory and Systems Genomics research group, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Zhen Shao shaozhen@sinh.ac.cn Investigator
Regulatory and Systems Genomics research group, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
Community Ratings
Usability | Efficiency | Reliability | Rated By |
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Accession | BT007339 |
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Tool Type | Toolkit |
Category | Normalization, Differential peak calling |
Platforms | Linux/Unix, MAC OS X, Windows |
Technologies | R |
User Interface | Terminal Command Line |
Latest Release | 1.2.2 (January 16, 2023) |
Download Count | 518 |
Country/Region | China |
Submitted By | Shiqi Tu |
National Basic Research Program of China: 2018YFA0107602, 2018YFA0800203; National Natural Science Foundation of China: 31871280, 31701140; “100-Talent Program” of the Chinese Academy of Sciences: Y516C11851; Strategic Priority Research Program of Chinese Academy of Sciences: XDB38040100.